What are the hardware requirements for Deepseek Qwen2.5 7B Baseline Thin Init?

Deepseek Qwen2.5 7B Baseline Thin Init requires approximately 31.3 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Deepseek Qwen2.5 7B Baseline Thin Init and how large is it?

Deepseek Qwen2.5 7B Baseline Thin Init is developed by hdong0, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Deepseek Qwen2.5 7B Baseline Thin Init?

Deepseek Qwen2.5 7B Baseline Thin Init is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Deepseek Qwen2.5 7B Baseline Thin Init by hdong0 — VRAM 31.3GB, 128K context

Name: Deepseek Qwen2.5 7B Baseline Thin Init
Author: hdong0

Deepseek Qwen2.5 7B Baseline Thin Init is an open-source language model by hdong0. Features: 7b LLM, VRAM: 31.3GB, Context: 128K, LLM Explorer Score: 0.18.

Arxiv:1910.09700 Conversational Custom code Qwen2bm Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/hdong0/deepseek-Qwen2.5-7B-baseline-thin-init

Deepseek Qwen2.5 7B Baseline Thin Init Parameters and Internals

LLM Name	Deepseek Qwen2.5 7B Baseline Thin Init
Repository 🤗	https://huggingface.co/hdong0/deepseek-Qwen2.5-7B-baseline-thin-init
Model Size	7b
Required VRAM	31.3 GB
Updated	2026-08-07
Maintainer	hdong0
Model Type	qwen2bm
Model Files	4.8 GB: 1-of-7 4.8 GB: 2-of-7 4.8 GB: 3-of-7 4.8 GB: 4-of-7 4.8 GB: 5-of-7 4.8 GB: 6-of-7 2.5 GB: 7-of-7
Model Architecture	Qwen2BMForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.52.0.dev0
Tokenizer Class	LlamaTokenizerFast
Padding Token	<｜end▁of▁sentence｜>
Vocabulary Size	152064
Torch Data Type	float32

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